Benjamin Schwarz, Mourad Zoubir, Jan Heidinger, Marthe Gruner, Hans-christian Jetter, Thomas Franke
To increase energy-efficiency and reduce CO2e emissions in maritime shipping, Decision-Support Systems (DSS) can be leveraged. Specifically, in regard to reducing the greatest contributor to consumption, propulsion (IMO, 2021), by assisting seafarers in route planning, and timely and efficient re-planning, as well as general monitoring of ship’s energy dynamics. However, the successful integration and acceptance of these systems into the seafarer’s workflow pose significant challenges, such as goal conflicts, e.g. with safety or with the financial interests of different stakeholders, which require a deep understanding of interactions onboard and onshore.This paper reflects on our implementation of a transdisciplinary design research approach for developing novel, human-centered AI-based tools for energy-efficient ship operations. Of our concurrent studies, we describe selected forms of inquiry that together resulted in a holistic understanding of the application domain, target audience, and typical tasks as well as an interactive prototype of a decision support system for energy-efficient ship navigation.The research activities reported are based on human factors research concerning energy-efficient ship operations and focus on research through design in the sense of Jonas (2015) in the field of DSS for CO2e emission mitigation in navigation and ship operation, and the formative evaluation of a DSS prototype in a ship simulator environment (N = 22). By viewing these research activities through the lens of design research, more specifically the theoretical foundation of MAPS (Jonas et al., 2010), we systematically describe and discuss their individual contributions. MAPS specifically operationalized design research as “Matching Analysis, Projection and Synthesis”, enabling integrative, systematic research processes across boundaries of disciplinary bodies of knowledge, domains and actors.As a primary contribution, we reflect on our lessons learned to identify generalizable challenges for similar future projects of the maritime ergonomics community. These include (1) context-sensitive integration of navigational and operational data; (2) calibration of users’ expectations of the system’s capabilities; and related to this (3) increasing transparency of how the DSS retrieves and processes data, and of how confident it is in its suggestions. By considering key human factors, such as workload, autonomy and biases (e.g., automation bias) on the basis of our system, we demonstrate how these challenges can be addressed. As a secondary contribution, we also share our resulting designs as examples of how AI-based decision support for optimizing energy efficiency can be visually and functionally integrated into onboard ship operation and navigation.REFERENCESIMO, 2021. Fourth IMO GHG Study 2020. International Maritime Organization, London, UK.Jonas, W., 2015. Research through design is more than just a new form of disseminating design outcomes. Constructivis
{"title":"Investigating Challenges in Decision Support Systems for Energy-Efficient Ship Operation: A Transdisciplinary Design Research Approach","authors":"Benjamin Schwarz, Mourad Zoubir, Jan Heidinger, Marthe Gruner, Hans-christian Jetter, Thomas Franke","doi":"10.54941/ahfe1004281","DOIUrl":"https://doi.org/10.54941/ahfe1004281","url":null,"abstract":"To increase energy-efficiency and reduce CO2e emissions in maritime shipping, Decision-Support Systems (DSS) can be leveraged. Specifically, in regard to reducing the greatest contributor to consumption, propulsion (IMO, 2021), by assisting seafarers in route planning, and timely and efficient re-planning, as well as general monitoring of ship’s energy dynamics. However, the successful integration and acceptance of these systems into the seafarer’s workflow pose significant challenges, such as goal conflicts, e.g. with safety or with the financial interests of different stakeholders, which require a deep understanding of interactions onboard and onshore.This paper reflects on our implementation of a transdisciplinary design research approach for developing novel, human-centered AI-based tools for energy-efficient ship operations. Of our concurrent studies, we describe selected forms of inquiry that together resulted in a holistic understanding of the application domain, target audience, and typical tasks as well as an interactive prototype of a decision support system for energy-efficient ship navigation.The research activities reported are based on human factors research concerning energy-efficient ship operations and focus on research through design in the sense of Jonas (2015) in the field of DSS for CO2e emission mitigation in navigation and ship operation, and the formative evaluation of a DSS prototype in a ship simulator environment (N = 22). By viewing these research activities through the lens of design research, more specifically the theoretical foundation of MAPS (Jonas et al., 2010), we systematically describe and discuss their individual contributions. MAPS specifically operationalized design research as “Matching Analysis, Projection and Synthesis”, enabling integrative, systematic research processes across boundaries of disciplinary bodies of knowledge, domains and actors.As a primary contribution, we reflect on our lessons learned to identify generalizable challenges for similar future projects of the maritime ergonomics community. These include (1) context-sensitive integration of navigational and operational data; (2) calibration of users’ expectations of the system’s capabilities; and related to this (3) increasing transparency of how the DSS retrieves and processes data, and of how confident it is in its suggestions. By considering key human factors, such as workload, autonomy and biases (e.g., automation bias) on the basis of our system, we demonstrate how these challenges can be addressed. As a secondary contribution, we also share our resulting designs as examples of how AI-based decision support for optimizing energy efficiency can be visually and functionally integrated into onboard ship operation and navigation.REFERENCESIMO, 2021. Fourth IMO GHG Study 2020. International Maritime Organization, London, UK.Jonas, W., 2015. Research through design is more than just a new form of disseminating design outcomes. Constructivis","PeriodicalId":470195,"journal":{"name":"AHFE international","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135263861","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Hector Rafael Morano-okuno, Rafael Caltenco Castillo, Guillermo Sandoval
In the 2000s, the application of collaborative robots began to be heard more frequently in various sectors, such as the Manufacturing industry and Healthcare. One of its main advantages is the way of interacting with the user; since it allows to share workspaces more closely without any fatal collisions. Currently, the price of these robots varies with the task type; the more transport load they support and the greater precision in their movements, the more expensive they will be. Nowadays, several works mention the use of collaborative robots to assist in the rehabilitation process of patients. These procedures are expensive since, initially, the purchase of the robot is required, and later the application software to generate the patient's rehabilitation movements. This article presents a methodology to generate the trajectory of the rehabilitation movements of patients with limitations in the upper joints. Engineering application software is used for the academic community (Professors and students). The licenses for operating this software application are free for the academy. In university courses, inverse kinematics projects of collaborative robots can be proposed to generate the rehabilitation trajectories of the patients mentioned above. With this methodology, only the collaborative robot would be required, reducing the initial investment of this type of treatment. When using student software applications, it would be possible to use the other tools that this type of computational tool has, such as 3D printing of parts, some ergonomic analysis of components, or the design of parts or fasteners through the finite element method. To test the methodology developed, a case study was used. It was a final project in the Automation of Manufacturing Systems course of the Tecnologico de Monterrey for students of the Mechatronics Engineering career. In this case study, the generated trajectories stimulate patients' motor skills to draw 2D contours. However, an advantage of the described methodology is that it can be used to generate any 2D or 3D trajectory as required by the patient. The methodology consists of the following stages, 1) 3D modeling of the parts of the collaborative robot that intervenes to generate trajectories, 2) consultation of the reference system of the axes of the collaborative robot, 3) definition of the appropriate movements for the rehabilitation of the patient and 4) programming of the robot. At the beginning of the article, different configurations and applications of collaborative robots are mentioned. Subsequently, the characteristics of the collaborative robot used for this work are described. Next, the methodology implemented for generating trajectories for rehabilitating patients with limitations of the movements of the upper limbs is detailed. Then, the developed methodology is implemented through a case study. Finally, the results, conclusions, and future work are presented.
{"title":"Use of collaborative robots to generate movement trajectories for rehabilitating patients with joint mobility limitations of the upper extremities.","authors":"Hector Rafael Morano-okuno, Rafael Caltenco Castillo, Guillermo Sandoval","doi":"10.54941/ahfe1004413","DOIUrl":"https://doi.org/10.54941/ahfe1004413","url":null,"abstract":"In the 2000s, the application of collaborative robots began to be heard more frequently in various sectors, such as the Manufacturing industry and Healthcare. One of its main advantages is the way of interacting with the user; since it allows to share workspaces more closely without any fatal collisions. Currently, the price of these robots varies with the task type; the more transport load they support and the greater precision in their movements, the more expensive they will be. Nowadays, several works mention the use of collaborative robots to assist in the rehabilitation process of patients. These procedures are expensive since, initially, the purchase of the robot is required, and later the application software to generate the patient's rehabilitation movements. This article presents a methodology to generate the trajectory of the rehabilitation movements of patients with limitations in the upper joints. Engineering application software is used for the academic community (Professors and students). The licenses for operating this software application are free for the academy. In university courses, inverse kinematics projects of collaborative robots can be proposed to generate the rehabilitation trajectories of the patients mentioned above. With this methodology, only the collaborative robot would be required, reducing the initial investment of this type of treatment. When using student software applications, it would be possible to use the other tools that this type of computational tool has, such as 3D printing of parts, some ergonomic analysis of components, or the design of parts or fasteners through the finite element method. To test the methodology developed, a case study was used. It was a final project in the Automation of Manufacturing Systems course of the Tecnologico de Monterrey for students of the Mechatronics Engineering career. In this case study, the generated trajectories stimulate patients' motor skills to draw 2D contours. However, an advantage of the described methodology is that it can be used to generate any 2D or 3D trajectory as required by the patient. The methodology consists of the following stages, 1) 3D modeling of the parts of the collaborative robot that intervenes to generate trajectories, 2) consultation of the reference system of the axes of the collaborative robot, 3) definition of the appropriate movements for the rehabilitation of the patient and 4) programming of the robot. At the beginning of the article, different configurations and applications of collaborative robots are mentioned. Subsequently, the characteristics of the collaborative robot used for this work are described. Next, the methodology implemented for generating trajectories for rehabilitating patients with limitations of the movements of the upper limbs is detailed. Then, the developed methodology is implemented through a case study. Finally, the results, conclusions, and future work are presented.","PeriodicalId":470195,"journal":{"name":"AHFE international","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135313181","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
To improve sleep habits, we will create messages to raise awareness of sleep and examine the effects of messaging on sleep habits. Japanese people, especially children, and workers, sleep less than their counterparts, both men and women, in other countries. As a result, some people "sleep in on weekends," getting a lot of sleep on weekends to secure more sleep. Then, the rhythm becomes disturbed, and it becomes challenging to re-synchronize with the schedule. Therefore, it is necessary to improve sleeping habits to secure a certain amount of sleep. This study will utilize a messaging approach, gain/loss-framing messages. Then, we will investigate which message is more effective for sleep habits according to each participant's values about sleep. This experiment first administered a questionnaire to 130 college students and adults to assess their attitudes and values toward sleep. We conducted an exploratory factor analysis of 83 items of the questionnaire. As a result, factor scores were calculated for each respondent, and a total of six clusters were determined by cluster analysis. For the experiment, a total of 10 participants (college students in their 20s), five each with high factor scores, were selected from the "sleep-oriented" and "sleep-unoriented" types. The selected participants wore wristwatch-type terminals and went to bed after checking the messages sent to them. Participants received each of seven different kinds of gain/loss-framing messages per week. In questionnaires on 14 different messages, participants responded to the acceptability of the messages and changes in their attitudes toward sleep, such as going to bed early, getting up early, and reviewing their daily rhythms. A two-way ANOVA was conducted at the 5% significance level on the change in sleep awareness after confirmation of the sent message and on the evaluation of the acceptability of the sent message. We identified significant differences in sleep awareness in the main effects between clusters and in the interaction between clusters and message type. Sleep-oriented types tended to report more change in sleep awareness with loss-framing messages. In comparison, sleep-unoriented types tended to report more change in sleep awareness with gain-framing messages. Mean sleep time (minutes) during each period was calculated for each participant, and a two-way ANOVA was performed with message content and clusters as factors at a 5% significance level. We didn't find significant differences between clusters, message types, or interactions. However, sleep-oriented types tended to sleep longer than sleep-unoriented types. Furthermore, in both clusters, sleep duration tended to be longer in weeks when they received loss-framing messages than in weeks when they received gain-framing messages. The interventions in this study produced changes in sleep attitudes, but these changes differed across clusters. On the other hand, all clusters showed a trend toward longer sleep duration
{"title":"Effects of Gain/Loss Messages on Reinforcing Motivation to Sleep","authors":"Shugo Ono, Aoi Nambu, Kouki Kamada, Toru Nakata, Takashi Sakamoto, Toshikazu Kato","doi":"10.54941/ahfe1004206","DOIUrl":"https://doi.org/10.54941/ahfe1004206","url":null,"abstract":"To improve sleep habits, we will create messages to raise awareness of sleep and examine the effects of messaging on sleep habits. Japanese people, especially children, and workers, sleep less than their counterparts, both men and women, in other countries. As a result, some people \"sleep in on weekends,\" getting a lot of sleep on weekends to secure more sleep. Then, the rhythm becomes disturbed, and it becomes challenging to re-synchronize with the schedule. Therefore, it is necessary to improve sleeping habits to secure a certain amount of sleep. This study will utilize a messaging approach, gain/loss-framing messages. Then, we will investigate which message is more effective for sleep habits according to each participant's values about sleep. This experiment first administered a questionnaire to 130 college students and adults to assess their attitudes and values toward sleep. We conducted an exploratory factor analysis of 83 items of the questionnaire. As a result, factor scores were calculated for each respondent, and a total of six clusters were determined by cluster analysis. For the experiment, a total of 10 participants (college students in their 20s), five each with high factor scores, were selected from the \"sleep-oriented\" and \"sleep-unoriented\" types. The selected participants wore wristwatch-type terminals and went to bed after checking the messages sent to them. Participants received each of seven different kinds of gain/loss-framing messages per week. In questionnaires on 14 different messages, participants responded to the acceptability of the messages and changes in their attitudes toward sleep, such as going to bed early, getting up early, and reviewing their daily rhythms. A two-way ANOVA was conducted at the 5% significance level on the change in sleep awareness after confirmation of the sent message and on the evaluation of the acceptability of the sent message. We identified significant differences in sleep awareness in the main effects between clusters and in the interaction between clusters and message type. Sleep-oriented types tended to report more change in sleep awareness with loss-framing messages. In comparison, sleep-unoriented types tended to report more change in sleep awareness with gain-framing messages. Mean sleep time (minutes) during each period was calculated for each participant, and a two-way ANOVA was performed with message content and clusters as factors at a 5% significance level. We didn't find significant differences between clusters, message types, or interactions. However, sleep-oriented types tended to sleep longer than sleep-unoriented types. Furthermore, in both clusters, sleep duration tended to be longer in weeks when they received loss-framing messages than in weeks when they received gain-framing messages. The interventions in this study produced changes in sleep attitudes, but these changes differed across clusters. On the other hand, all clusters showed a trend toward longer sleep duration","PeriodicalId":470195,"journal":{"name":"AHFE international","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135313222","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The meaning of visual imagery encapsulates the essence of the era's aspirations. This meaning can vary across different cultures, and metaphorical expressions can also differ significantly. Throughout history, the evolution of images has experienced diverse transformations. In the present day, these images continue to undergo digitization, evolving their meanings through various markets and novel formats. As an illustration, the convergence of art, photography, and the implementation of smart contracts in the form of Non-Fungible Tokens (NFTs) has gained momentum alongside virtual currencies like Bitcoin, serving as a digital means of value exchange.Personal experiences contribute to elevating the value of images, and the subjective nature of value assessment criteria has spurred considerable discourse on valuation methods and problem-solving approaches. In a reality lacking precise standards, both significant and minor societal side effects arise. Moreover, challenges to sustainability and environmental threats have also emerged. In the realm of design, endeavors such as design thinking, speculative design envisioning future scenarios, and design futuring have been employed as alternative approaches to address these issues. These novel design attempts have garnered attention as methods for embracing uncertainties about the future and the consequent problem-solving efforts.Against this backdrop, this study aims to pose the question of how metaphoric images, particularly NFTs, will evolve in the future. As a means of seeking answers, the research intends to explore the value inherent in images by investigating prior studies on their meanings across the past, present, and future. Additionally, the metaphorical expressions embedded in these images will be examined for the implied significations they carry. Furthermore, the trajectory of these images from their origins to their current state will be traced, delving into the frequency of use across cultural and societal strata, as well as the utilization of digital imagery following its establishment in the digital realm.This research will not merely focus on the transformation of artists' and designers' creations into NFTs but will also scrutinize how digital images in the new era acquire value and meaning. Ultimately, it aims to comprehensively explore the implications of future metaphoric images, particularly in the context of NFTs and their connection to human culture. Additionally, the study will examine instances where societal institutions impact NFTs' digital images and reciprocally, where these images influence societal norms. This exploration will encompass the analysis of different nations, epochs, and the digital convergence era. In summation, the synthesized findings will categorize the meanings associated with these images and investigate how they can genuinely add value via historical research, or case studies.
{"title":"Future Image making in the era of Metaverse: Focus on Non-Fungible Tokens and the Future of Art","authors":"Young Jun Han","doi":"10.54941/ahfe1004456","DOIUrl":"https://doi.org/10.54941/ahfe1004456","url":null,"abstract":"The meaning of visual imagery encapsulates the essence of the era's aspirations. This meaning can vary across different cultures, and metaphorical expressions can also differ significantly. Throughout history, the evolution of images has experienced diverse transformations. In the present day, these images continue to undergo digitization, evolving their meanings through various markets and novel formats. As an illustration, the convergence of art, photography, and the implementation of smart contracts in the form of Non-Fungible Tokens (NFTs) has gained momentum alongside virtual currencies like Bitcoin, serving as a digital means of value exchange.Personal experiences contribute to elevating the value of images, and the subjective nature of value assessment criteria has spurred considerable discourse on valuation methods and problem-solving approaches. In a reality lacking precise standards, both significant and minor societal side effects arise. Moreover, challenges to sustainability and environmental threats have also emerged. In the realm of design, endeavors such as design thinking, speculative design envisioning future scenarios, and design futuring have been employed as alternative approaches to address these issues. These novel design attempts have garnered attention as methods for embracing uncertainties about the future and the consequent problem-solving efforts.Against this backdrop, this study aims to pose the question of how metaphoric images, particularly NFTs, will evolve in the future. As a means of seeking answers, the research intends to explore the value inherent in images by investigating prior studies on their meanings across the past, present, and future. Additionally, the metaphorical expressions embedded in these images will be examined for the implied significations they carry. Furthermore, the trajectory of these images from their origins to their current state will be traced, delving into the frequency of use across cultural and societal strata, as well as the utilization of digital imagery following its establishment in the digital realm.This research will not merely focus on the transformation of artists' and designers' creations into NFTs but will also scrutinize how digital images in the new era acquire value and meaning. Ultimately, it aims to comprehensively explore the implications of future metaphoric images, particularly in the context of NFTs and their connection to human culture. Additionally, the study will examine instances where societal institutions impact NFTs' digital images and reciprocally, where these images influence societal norms. This exploration will encompass the analysis of different nations, epochs, and the digital convergence era. In summation, the synthesized findings will categorize the meanings associated with these images and investigate how they can genuinely add value via historical research, or case studies.","PeriodicalId":470195,"journal":{"name":"AHFE international","volume":"121 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135316640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
"Industry 4.0," initially a German initiative focused on technological advancements within the industrial sector, has garnered global recognition. Other nations have also initiated similar strategic endeavours, leading to extensive research dedicated to the development and implementation of Industry 4.0 technologies. More recently, the European Commission introduced "Industry 5.0," a decade following the inception of Industry 4.0. While Industry 4.0 is commonly perceived as technology-driven, Industry 5.0 is heralded as value-driven. The coexistence of these two industrial revolutions has spurred significant debates and necessitates thorough explanations. The business sector plays a pivotal role in fostering economic growth. However, the integration of new technology and the growing complexity of products and production processes have direct repercussions on industrial companies and their workforce. Critics of the Industry 4.0 paradigm underscore its technocratic focus on digitalization and novel technologies. Consequently, when Industry 5.0 emerged, discussions regarding its function and rationale gained rapid prominence. Industry 5.0 complements Industry 4.0, emphasizing the pivotal role of workers in the industrial process. Industry 4.0 has facilitated remarkable technological advancements, including additive manufacturing, artificial intelligence, augmented reality, cyber-physical systems, blockchain, and cybersecurity. These technologies address issues like demand fluctuations and market instability by minimizing human involvement in decision-making through the integration of computers, materials, and AI. Nonetheless, Industry 4.0 must surmount challenges in data security, supply chain management, human resource administration, and technological integration. In contrast, Industry 5.0 tackles these challenges with innovations such as predictive maintenance, hyper-customization, cyber-physical cognitive systems, and collaborative robots, placing a strong emphasis on human-centricity. The introduction of Industry 5.0 heralds an anticipated paradigm shift, prioritizing holistic, sustainable, and human-centered value generation. However, the escalating complexity of digitalization poses considerable difficulties, particularly for small and medium-sized businesses (SMEs) with limited resources for effective digitalization initiatives. This study delves into the literature surrounding improvements for both Industry 4.0 and Industry 5.0, addressing issues such as data privacy and technical integration problems. In Industry 5.0, resilience emerges as a crucial factor in enabling hyper-individualization and customized product offerings. Additionally, this study provides a concise exploration of the primary drivers and facilitators of the adoption of these new paradigms. It subsequently conducts a literature-based analysis, examining how these two paradigms differ from three essential perspectives: people, technology, and organizations. Moreover, it of
{"title":"The Paradigm Shift from Industry 4.0 Implementation to Industry 5.0 Readiness","authors":"Arvin Shadravan, Hamid Parsaei","doi":"10.54941/ahfe1004296","DOIUrl":"https://doi.org/10.54941/ahfe1004296","url":null,"abstract":"\"Industry 4.0,\" initially a German initiative focused on technological advancements within the industrial sector, has garnered global recognition. Other nations have also initiated similar strategic endeavours, leading to extensive research dedicated to the development and implementation of Industry 4.0 technologies. More recently, the European Commission introduced \"Industry 5.0,\" a decade following the inception of Industry 4.0. While Industry 4.0 is commonly perceived as technology-driven, Industry 5.0 is heralded as value-driven. The coexistence of these two industrial revolutions has spurred significant debates and necessitates thorough explanations. The business sector plays a pivotal role in fostering economic growth. However, the integration of new technology and the growing complexity of products and production processes have direct repercussions on industrial companies and their workforce. Critics of the Industry 4.0 paradigm underscore its technocratic focus on digitalization and novel technologies. Consequently, when Industry 5.0 emerged, discussions regarding its function and rationale gained rapid prominence. Industry 5.0 complements Industry 4.0, emphasizing the pivotal role of workers in the industrial process. Industry 4.0 has facilitated remarkable technological advancements, including additive manufacturing, artificial intelligence, augmented reality, cyber-physical systems, blockchain, and cybersecurity. These technologies address issues like demand fluctuations and market instability by minimizing human involvement in decision-making through the integration of computers, materials, and AI. Nonetheless, Industry 4.0 must surmount challenges in data security, supply chain management, human resource administration, and technological integration. In contrast, Industry 5.0 tackles these challenges with innovations such as predictive maintenance, hyper-customization, cyber-physical cognitive systems, and collaborative robots, placing a strong emphasis on human-centricity. The introduction of Industry 5.0 heralds an anticipated paradigm shift, prioritizing holistic, sustainable, and human-centered value generation. However, the escalating complexity of digitalization poses considerable difficulties, particularly for small and medium-sized businesses (SMEs) with limited resources for effective digitalization initiatives. This study delves into the literature surrounding improvements for both Industry 4.0 and Industry 5.0, addressing issues such as data privacy and technical integration problems. In Industry 5.0, resilience emerges as a crucial factor in enabling hyper-individualization and customized product offerings. Additionally, this study provides a concise exploration of the primary drivers and facilitators of the adoption of these new paradigms. It subsequently conducts a literature-based analysis, examining how these two paradigms differ from three essential perspectives: people, technology, and organizations. Moreover, it of","PeriodicalId":470195,"journal":{"name":"AHFE international","volume":"162 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135316648","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Daniel Pittman, Kerstin Haring, Chris Gauthierdickey
This paper proposes the innovative use of Multi-User Dungeons (MUDs) as a testbed for exploring and refining Artificial Intelligence (AI) ethics in decision support systems. MUDs are interactive, text-based virtual environments and offer a unique platform for studying AI behavior in a controlled yet complex environment. Our approach involves a combination of machine learning and natural language processing techniques to implement AI as a decision support system, and designs scenarios that challenge players with ethical quandaries and dilemmas. The effectiveness and ethical decision-making of players, the AI, and both together as a team are evaluated through a mix of quantitative and qualitative methods. The approaches detailed in this research aim to contribute to the broader discourse on AI ethics, stimulate a discussion on how to provide empirical evidence of AI decision-making's impact on human behavior in MUDs, and informing the design of ethically responsible AI systems in other domains.
{"title":"Leveraging Multi-User Dungeons for Ethical AI Decision Support Systems: A Novel Approach","authors":"Daniel Pittman, Kerstin Haring, Chris Gauthierdickey","doi":"10.54941/ahfe1004180","DOIUrl":"https://doi.org/10.54941/ahfe1004180","url":null,"abstract":"This paper proposes the innovative use of Multi-User Dungeons (MUDs) as a testbed for exploring and refining Artificial Intelligence (AI) ethics in decision support systems. MUDs are interactive, text-based virtual environments and offer a unique platform for studying AI behavior in a controlled yet complex environment. Our approach involves a combination of machine learning and natural language processing techniques to implement AI as a decision support system, and designs scenarios that challenge players with ethical quandaries and dilemmas. The effectiveness and ethical decision-making of players, the AI, and both together as a team are evaluated through a mix of quantitative and qualitative methods. The approaches detailed in this research aim to contribute to the broader discourse on AI ethics, stimulate a discussion on how to provide empirical evidence of AI decision-making's impact on human behavior in MUDs, and informing the design of ethically responsible AI systems in other domains.","PeriodicalId":470195,"journal":{"name":"AHFE international","volume":"150 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135262411","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Core body temperature (CBT) is an important health indicator that denotes the temperature of the body core, and maintains brain and organ function. Invasive methods of CBT measurement pose challenges in assessing and monitoring human health. To address this, estimation of tympanic membrane temperature using multiple biological parameters often referenced for CBT has been attempted in previous studies. Our research focused on machine learning-based CBT estimation using hand-measurable biological data. Furthermore, while various studies have investigated machine learning models and the impact of information acquisition environments, few have compared the estimation accuracy of different biological parameters or assessed optimal feature combinations. Our proposed method entails the evaluation of indices in both normal scenarios with all variables and patterned scenarios with varying combinations of reduced explanatory variables. The comparison results reveal that when estimating the CBT based on skin conductance and pulse wave intervals excluding skin temperature, the mean absolute error, coefficient of determination, and root mean square error were 0.17 °C, 0.71, and 0.24 °C, respectively. This suggests that our approach is a feasible CBT estimation method that does not rely on skin temperature, although accuracy concerns persist. Furthermore, the estimation of the difference between CBT and skin temperature suggests that the estimation method may have accounted for individual variations within the data. Implementing the proposed method in increasingly popular smart rings and watches could facilitate the acquisition of CBT in daily life.
{"title":"Feature Selection for Machine Learning-Based Core Body Temperature Estimation Using Hand-Measurable Biological Information","authors":"Ryoya Oba, Keiichi Watanuki, Kazunori Kaede, Yusuke Osawa","doi":"10.54941/ahfe1004362","DOIUrl":"https://doi.org/10.54941/ahfe1004362","url":null,"abstract":"Core body temperature (CBT) is an important health indicator that denotes the temperature of the body core, and maintains brain and organ function. Invasive methods of CBT measurement pose challenges in assessing and monitoring human health. To address this, estimation of tympanic membrane temperature using multiple biological parameters often referenced for CBT has been attempted in previous studies. Our research focused on machine learning-based CBT estimation using hand-measurable biological data. Furthermore, while various studies have investigated machine learning models and the impact of information acquisition environments, few have compared the estimation accuracy of different biological parameters or assessed optimal feature combinations. Our proposed method entails the evaluation of indices in both normal scenarios with all variables and patterned scenarios with varying combinations of reduced explanatory variables. The comparison results reveal that when estimating the CBT based on skin conductance and pulse wave intervals excluding skin temperature, the mean absolute error, coefficient of determination, and root mean square error were 0.17 °C, 0.71, and 0.24 °C, respectively. This suggests that our approach is a feasible CBT estimation method that does not rely on skin temperature, although accuracy concerns persist. Furthermore, the estimation of the difference between CBT and skin temperature suggests that the estimation method may have accounted for individual variations within the data. Implementing the proposed method in increasingly popular smart rings and watches could facilitate the acquisition of CBT in daily life.","PeriodicalId":470195,"journal":{"name":"AHFE international","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135263248","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Human-computer interface (HCI) design is an essential aspect of modern technology development, which involves the interaction between humans and computers. HCI design can pose legal risks that may result in significant legal liabilities and consequences for any organization adopting the designs. From the standpoint of an HCI designer as opposed to a legal researcher, this article analyzes the legal risks underlying HCI design and the related regulatory framework in the small jurisdiction Macao in comparison with those in some major jurisdictions, including the United States, the European Union (EU), and mainland China. Relevant statutes, acts, and academic literature are drawn on to support the analysis. Categories of the aforesaid risks are primarily identified as intellectual property, privacy and personal data protection, accessibility, liability for harm, and cybersecurity breaches, only the first two of which are to be elucidated in this article due to its length limitation. The following findings are highlighted: Macao’s IP regime does not include provisions very specific to HCI designs, unlike the United States, the EU, and mainland China. Macao’s privacy and personal data protection framework is less comprehensive than the General Data Protection Regulation (GDPR) in the EU and mainland China’s Cybersecurity Law, Personal Information Protection Law (PIPL), and Data Security Law (DSL). In particular, the GDPR additionally mandates “data protection by design and default,” and mainland China’s Cybersecurity Law, PIPL, and DSL are well integrated with cyberspace sovereignty, national security, social and public interests, national sovereignty, and development interests of the state. In summary, in principle, the legal framework in the small jurisdiction Macao governing the legal risks associated with HCI is by and large in line with those in major and substantially larger jurisdictions. Notwithstanding, the former is in general a general miniature of the latter and comparatively devoid of express provisions very specific to and comprehensively covering HCI design. Subject to further research’s confirmation, this phenomenon of generalization and miniaturization may be true of many other small jurisdictions worldwide as reasoned in this article.
{"title":"Legal Risks Underlying Human-Computer interface (HCI) Design: A Comparative Study on Macao vs. Major Jurisdictions","authors":"Victor K Y Chan","doi":"10.54941/ahfe1004239","DOIUrl":"https://doi.org/10.54941/ahfe1004239","url":null,"abstract":"Human-computer interface (HCI) design is an essential aspect of modern technology development, which involves the interaction between humans and computers. HCI design can pose legal risks that may result in significant legal liabilities and consequences for any organization adopting the designs. From the standpoint of an HCI designer as opposed to a legal researcher, this article analyzes the legal risks underlying HCI design and the related regulatory framework in the small jurisdiction Macao in comparison with those in some major jurisdictions, including the United States, the European Union (EU), and mainland China. Relevant statutes, acts, and academic literature are drawn on to support the analysis. Categories of the aforesaid risks are primarily identified as intellectual property, privacy and personal data protection, accessibility, liability for harm, and cybersecurity breaches, only the first two of which are to be elucidated in this article due to its length limitation. The following findings are highlighted: Macao’s IP regime does not include provisions very specific to HCI designs, unlike the United States, the EU, and mainland China. Macao’s privacy and personal data protection framework is less comprehensive than the General Data Protection Regulation (GDPR) in the EU and mainland China’s Cybersecurity Law, Personal Information Protection Law (PIPL), and Data Security Law (DSL). In particular, the GDPR additionally mandates “data protection by design and default,” and mainland China’s Cybersecurity Law, PIPL, and DSL are well integrated with cyberspace sovereignty, national security, social and public interests, national sovereignty, and development interests of the state. In summary, in principle, the legal framework in the small jurisdiction Macao governing the legal risks associated with HCI is by and large in line with those in major and substantially larger jurisdictions. Notwithstanding, the former is in general a general miniature of the latter and comparatively devoid of express provisions very specific to and comprehensively covering HCI design. Subject to further research’s confirmation, this phenomenon of generalization and miniaturization may be true of many other small jurisdictions worldwide as reasoned in this article.","PeriodicalId":470195,"journal":{"name":"AHFE international","volume":"29 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135311155","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
In this study, we aimed to clarify the characteristics of cerebral blood flow during the N-back task for males and for females in the follicular and luteal phases. Near infrared spectroscopy (NIRS) was used to measure Oxyhemoglobin (Oxy-Hb) in the prefrontal cortex during the N-back task. In the analysis, the prefrontal cortex was divided into right and left regions, and the integrated Oxy-Hb value, center of gravity value, and activation rate (initial activation) in the first 5 seconds of the task were calculated for each region. The percentage of correct responses to the N-back task was also calculated. Differences in each representative value among the three groups (follicular phase, luteal phase, and male) were examined. The task correct response rate was lowest in the luteal phase group for males and the luteal phase group (p<.05) and in the follicular phase group and the luteal phase group (p<.05). There were no significant differences between groups in integral and center-of-gravity values, and there were significant differences between groups in the initial activation of CH10-13 (left area) during the 2-back task (p<.05), with the lowest in the luteal phase group among males (p<.05), follicular phase group (p<.05) and luteal phase group (p<.05). A decrease in working memory is suggested in luteal phase women. This may be due to the presence of women with premenstrual syndrome symptoms or to sex hormone effects.
{"title":"Characteristics of Cerebral Blood Flow during Working Memory Tasks - Comparison of the follicular and luteal phases in females and males","authors":"Makiko Aoki, Satoshi Suzuki","doi":"10.54941/ahfe1004391","DOIUrl":"https://doi.org/10.54941/ahfe1004391","url":null,"abstract":"In this study, we aimed to clarify the characteristics of cerebral blood flow during the N-back task for males and for females in the follicular and luteal phases. Near infrared spectroscopy (NIRS) was used to measure Oxyhemoglobin (Oxy-Hb) in the prefrontal cortex during the N-back task. In the analysis, the prefrontal cortex was divided into right and left regions, and the integrated Oxy-Hb value, center of gravity value, and activation rate (initial activation) in the first 5 seconds of the task were calculated for each region. The percentage of correct responses to the N-back task was also calculated. Differences in each representative value among the three groups (follicular phase, luteal phase, and male) were examined. The task correct response rate was lowest in the luteal phase group for males and the luteal phase group (p<.05) and in the follicular phase group and the luteal phase group (p<.05). There were no significant differences between groups in integral and center-of-gravity values, and there were significant differences between groups in the initial activation of CH10-13 (left area) during the 2-back task (p<.05), with the lowest in the luteal phase group among males (p<.05), follicular phase group (p<.05) and luteal phase group (p<.05). A decrease in working memory is suggested in luteal phase women. This may be due to the presence of women with premenstrual syndrome symptoms or to sex hormone effects.","PeriodicalId":470195,"journal":{"name":"AHFE international","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135312942","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Artificial intelligence (AI) systems have increasingly been employed in various industries, including the laundry sector, e.g., to assist the employees sorting the laundry. This study aims to investigate the influence of image-based explanations on the acceptance of an AI system, by using CNNs that were trained to classify color and type of laundry items, with the explanations being generated through Deep Taylor Decomposition, a popular Explainable AI technique. We specifically examined how providing reasonable and unreasonable visual explanations affected the confidence levels of participating employees from laundries in their respective decisions. 32 participants were recruited from a diverse range of laundries, age, experience in this sector and prior experience with AI technologies and were invited to take part in this study. Each participant was presented with a set of 20 laundry classifications made by the AI system. They were then asked to indicate whether the accompanying image-based explanation strengthened or weakened their confidence in each decision. A five-level Likert scale was utilized to measure the impact, ranging from 1 (strongly weakens confidence) to 5 (strongly strengthens confidence). By providing visual cues and contextual information, the explanations are expected to enhance participants' understanding of the AI system's decision-making process. Consequently, we hypothesize that the image-based explanations will strengthen participants' confidence in the AI system's classifications, leading to increased acceptance and trust in its capabilities. The analysis of the results indicated significant main effects for both the quality of explanation and neural network certainties variables. Moreover, the interaction between explanation quality and neural network certainties also demonstrated a notable level of significance.The outcomes of this study hold substantial implications for the integration of AI systems within the laundry industry and other related domains. By identifying the influence of image-based explanations on acceptance, organizations can refine their AI implementations, ensuring effective utilization and positive user experiences. By fostering a better understanding of how image-based explanations influence AI acceptance, this study contributes to the ongoing development and improvement of AI systems across industries. Ultimately, this research seeks to pave the way for enhanced human-AI collaboration and more widespread adoption of AI technologies. Future research in this area could explore alternative forms of visual explanations, to further examine their impact on user acceptance and confidence in AI systems.
{"title":"Measuring the Impact of Picture-Based Explanations on the Acceptance of an AI System for Classifying Laundry","authors":"Nico Rabethge, Dominik Bentler","doi":"10.54941/ahfe1004181","DOIUrl":"https://doi.org/10.54941/ahfe1004181","url":null,"abstract":"Artificial intelligence (AI) systems have increasingly been employed in various industries, including the laundry sector, e.g., to assist the employees sorting the laundry. This study aims to investigate the influence of image-based explanations on the acceptance of an AI system, by using CNNs that were trained to classify color and type of laundry items, with the explanations being generated through Deep Taylor Decomposition, a popular Explainable AI technique. We specifically examined how providing reasonable and unreasonable visual explanations affected the confidence levels of participating employees from laundries in their respective decisions. 32 participants were recruited from a diverse range of laundries, age, experience in this sector and prior experience with AI technologies and were invited to take part in this study. Each participant was presented with a set of 20 laundry classifications made by the AI system. They were then asked to indicate whether the accompanying image-based explanation strengthened or weakened their confidence in each decision. A five-level Likert scale was utilized to measure the impact, ranging from 1 (strongly weakens confidence) to 5 (strongly strengthens confidence). By providing visual cues and contextual information, the explanations are expected to enhance participants' understanding of the AI system's decision-making process. Consequently, we hypothesize that the image-based explanations will strengthen participants' confidence in the AI system's classifications, leading to increased acceptance and trust in its capabilities. The analysis of the results indicated significant main effects for both the quality of explanation and neural network certainties variables. Moreover, the interaction between explanation quality and neural network certainties also demonstrated a notable level of significance.The outcomes of this study hold substantial implications for the integration of AI systems within the laundry industry and other related domains. By identifying the influence of image-based explanations on acceptance, organizations can refine their AI implementations, ensuring effective utilization and positive user experiences. By fostering a better understanding of how image-based explanations influence AI acceptance, this study contributes to the ongoing development and improvement of AI systems across industries. Ultimately, this research seeks to pave the way for enhanced human-AI collaboration and more widespread adoption of AI technologies. Future research in this area could explore alternative forms of visual explanations, to further examine their impact on user acceptance and confidence in AI systems.","PeriodicalId":470195,"journal":{"name":"AHFE international","volume":"86 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135317471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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